Cellular communications networks continue to experience rapid growth, with the volume of data traffic in mobile broadband (MBB) in particular increasing exponentially. Spectrum resources carrying MBB data are already congested, and it is likely that the frequency bands currently in use will be insufficient to support this increasing traffic in the coming years.
In addition to the growing volume of data traffic, the number of devices connected via cellular communications networks is also forecast to increase substantially in the near future, and it is expected that machine devices (MD) will contribute significantly to this forecast increase in connected devices. Machine devices are autonomous, often very small devices typically associated with equipment or apparatus as opposed to a human user. MDs use cellular or other types of communication networks to communicate with an application server, which may or may not be comprised within the cellular network. The application server receives information from the MD and configures the MD remotely. MDs thus typically access the cellular network more or less infrequently, transmitting and receiving very small amounts of data, or being polled for data. MDs represent a subset within the larger category of User Equipment devices (UEs), and may also be referred to as machine type communication (MTC) devices or machine to machine (M2M) devices. Massive machine communication (MMC) refers to the deployment of such devices on a very large scale, and MTC devices appropriate for such deployment may thus also be referred to as massive machine communication (MMC) devices.
In the context of the above discussed demands on spectrum resources for MBB traffic, identifying spectrum resources to support future large scale deployment of MMC devices is highly challenging. In addition, predicted scenarios for MMC deployment impose very high requirements on geographic coverage. For example, the “Massive deployment of sensors and actuators” test case in the EU project METIS (Mobile and wireless communications Enablers for the Twenty-twenty Information Society), imposes a coverage requirement of 99.99% of land area. It is highly unlikely that it will prove economically viable for network operators to support the site acquisition and other costs involved in enabling such coverage, particularly in remote areas where a site may be required to service only a small number of customers. Operation of MMC devices at lower frequency bands has been offered as a potential solution to this coverage problem. However, the lower region of the spectrum chart is very heavily congested, and the issue of spectrum resource allocation therefore remains highly challenging.
Opportunistic spectrum access, also known as cognitive radio, is an area of research seeking to achieve more efficient use of available spectrum bands. While promising results have been observed, the operation of opportunistic spectrum access is dependent upon extensive sensing and spectrum opportunity detection activities. The power consumed in conducting such activities would be highly detrimental to UE battery life. For MMC devices, which, owing to their nature and use patterns are required to be highly energy efficient, such power consumption would be devastating to device operational lifespan. Additional demands on battery power would also be contrary to the ongoing aim of improving battery life for UEs. For example, a goal of the EU METIS project is to achieve a ten times increase in device battery life.